AIMC Topic: Humans

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Assessing the effectiveness of fuzzy logic-based models for predicting sports event outcomes: A CRITIC-VIKOR approach.

PloS one
Incorporating fuzzy logic-based models into sports prediction has generated significant interest due to the intricate nature of athletic events and the many factors influencing their outcomes. This study evaluates the effectiveness of fuzzy logic-bas...

Machine learning-based urban noise appropriateness evaluation method and driving factor analysis.

PloS one
The evaluation of urban noise suitability is crucial for urban environmental management. Efficient and cost-effective methods for obtaining noise distribution data are of great interest. This study introduces various machine learning methods and appl...

Unveiling the intricate interplay: Exploring biological bridges between renal ischemia-reperfusion injury and T cell-mediated immune rejection in kidney transplantation.

PloS one
UNLABELLED: Although the link between ischemia-reperfusion injury (IRI) and T cell-mediated rejection (TCMR) in kidney transplantation (KT) is well known, the mechanism remains unclear. We investigated essential genes and biological processes involve...

Faecal metaproteomics analysis reveals a high cardiovascular risk profile across healthy individuals and heart failure patients.

Gut microbes
The gut microbiota is a crucial link between diet and cardiovascular disease (CVD). Using fecal metaproteomics, a method that concurrently captures human gut and microbiome proteins, we determined the crosstalk between gut microbiome, diet, gut healt...

Development and Validation of a Nomogram for Predicting Frailty Risk Among Older Patients With Ischaemic Stroke.

Journal of clinical nursing
AIM: To investigate the risk factors associated with frailty in older patients with ischaemic stroke, develop a nomogram and apply it clinically.

Anxiety about artificial intelligence from patient and doctor-physician.

Patient education and counseling
OBJECTIVE: This paper investigates the anxiety surrounding the integration of artificial intelligence (AI) in doctor-patient interactions, analyzing the perspectives of both patients and healthcare providers to identify key concerns and potential sol...

External validation of predictive models for antibiotic susceptibility of urine culture.

BJU international
OBJECTIVE: To develop, externally validate, and test a series of computer algorithms to accurately predict antibiotic susceptibility test (AST) results at the time of clinical diagnosis, up to 3 days before standard urine culture results become avail...

Decoding thoughts, encoding ethics: A narrative review of the BCI-AI revolution.

Brain research
OBJECTIVES: This narrative review aims to analyze mechanisms underlying Brain-Computer Interface (BCI) and Artificial Intelligence (AI) integration, evaluate recent advances in signal acquisition and processing techniques, and assess AI-enhanced neur...

Artificial intelligence education in medical imaging: A scoping review.

Journal of medical imaging and radiation sciences
BACKGROUND: The rise of Artificial intelligence (AI) is reshaping healthcare, particularly in medical imaging. In this emerging field, clinical imaging personnel need proper training. However, formal AI education is lacking in medical curricula, coup...

Accurate prediction of bleeding risk after coronary artery bypass grafting with dual antiplatelet therapy: A machine learning model vs. the PRECISE-DAPT score.

International journal of cardiology
BACKGROUND: Dual antiplatelet therapy (DAPT) after coronary artery bypass grafting (CABG), although might be protective for ischemic events, can lead to varying degrees of bleeding, resulting in serious clinical events, including death. This study ai...